[...] In practice, conventional controllers were used to control the system however their
parameters are empirically adjusted. Besides, the operation of these controllers relies on the
measurements provided by sensors located inside and near the greenhouse. If the
information provided by one or several of these sensors is erroneous, the controllers will not operate properly. Similarly, failure of one or several of the actuators to function
properly will impair the greenhouse operation. Therefore, an automatic diagnosis system of
failures in greenhouses is proposed. The diagnosis system is based on deviations observed
between measurements performed in the system and the predictions of a model of the
failure-free system. This comparison is done through a bank of fuzzy observers, where each
observer becomes active to a specific failure signature and inactive to the other failures.
Neural networks are used to develop a model for the failure-free greenhouse.
The main objective of this thesis is to explore and develop intelligent control schemes
for adjusting the climate inside a greenhouse. The thesis employs the conventional Pseudo-
Derivative Feedback (PDF) Controller. It develops the fuzzy PDF controller (FPDF). The
thesis also, develops two genetic algorithm (GA) based climatic control schemes, one is
genetic PDF (GPDF) and the other is genetic FPDF (GFPDF). The former uses GA to
adjust the gains of the Pseudo-Derivative Feedback Controller (GPDF) and the later uses
genetic algorithm to optimize the FPDF controller parameters (i.e., scale factors and/or
parameters of the membership functions). Finally, the thesis develops a fuzzy neural fault
detection and isolation system (FNFDIS), in which a bank of fuzzy observers are designed
to detect faults that may occur in the greenhouse end items (e.g.., sensors and actuators).
Simulation experiments are performed to test the soundness and capabilities of the
developed control schemes for controlling the greenhouse climate. The proposed schemes
are tested through two experiments, setpoint tracking test and regulatory control test. Also,
the proposed diagnostic system was tested through four experiments. Compared with the
results obtained using the conventional controllers, best results have been achieved using
the proposed control schemes.
Inhaltsverzeichnis (Table of Contents)
- Introduction
- Preliminaries
- The greenhouse climate: characteristics and determinism
- Research objectives
- Outline of the thesis
- Background to fuzzy logic, Neural Networks, Optimizers, Greenhouses and Fault Detection/Isolation Systems
- Preliminaries
- Fuzzy Logic Systems and their Applications
- Fuzzy sets and fuzzy logic
- Architecture of fuzzy logic systems
- Fuzzification interface
- Knowledge base
- Fuzzy approximate reasoning
- Defuzzification interface
- Fuzzy logic systems in control
- Static fuzzy logic systems
- Adaptive fuzzy logic systems
- Features and applications of fuzzy logic systems
- Adaptive control
- Feedforward neural networks
Zielsetzung und Themenschwerpunkte (Objectives and Key Themes)
This thesis explores the development of intelligent control schemes for adjusting the climate within a greenhouse. The primary objective is to improve the efficiency of plant production in greenhouses by effectively controlling key environmental factors such as temperature, humidity, and carbon dioxide concentration. Key themes investigated include:- Intelligent control strategies for greenhouse climate management.
- Application of fuzzy logic, neural networks, and genetic algorithms in greenhouse control systems.
- Development of a fuzzy neural fault detection and isolation system (FNFDIS) for greenhouse diagnostics.
- Performance evaluation of different control schemes through simulation experiments.
- Comparison of intelligent control schemes with conventional approaches.
Zusammenfassung der Kapitel (Chapter Summaries)
- Introduction: This chapter provides an introduction to the research, outlining the importance of environmental control in plant production and the challenges posed by greenhouse climate management. It defines the research objectives and presents the structure of the thesis.
- Background to fuzzy logic, Neural Networks, Optimizers, Greenhouses and Fault Detection/Isolation Systems: This chapter offers a comprehensive overview of key technologies and concepts relevant to the thesis, including fuzzy logic, neural networks, genetic algorithms, greenhouse systems, and fault detection/isolation systems. It discusses the fundamentals, applications, and limitations of each technology, laying a foundation for the subsequent chapters.
Schlüsselwörter (Keywords)
This thesis focuses on the development and application of intelligent control systems for greenhouse climate management. Key terms and concepts include fuzzy logic, neural networks, genetic algorithms, fault detection and isolation, greenhouse climate control, and plant production efficiency.- Quote paper
- Ibrahim A. Hameed (Author), 2005, Environmental Control for Plants using Intelligent Control Systems, Munich, GRIN Verlag, https://www.grin.com/document/190479